Instructions to use jhj0517/MusePose with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jhj0517/MusePose with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jhj0517/MusePose", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
All models related to MusePose.
There're 4 trained models for musepose
- denoising_unet.pth
- motion_module.pth
- pose_guider.pth
- reference_unet.pth
- dw-ll_ucoco_384.pth
- yolox_l_8x8_300e_coco.pth
- sd-image-variations-diffusers
- image_encoder
- sd-vae-ft-mse
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